AI AND WRITING EDUCATION: REVISION, AUTHORSHIP, AND LANGUAGE LEARNING

Abstract

The topic of generative artificial intelligence in writing instruction was examined through its implications for revision, authorship, and language learning. The research problem investigated how generative AI, when applied to writing instruction, influenced textual revision processes, authorship, and language learning, considering pedagogical challenges and didactic possibilities. The general objective was to analyze, based on academic literature, the contributions and limits of generative AI in writing instruction, with emphasis on revision, authorship, and language learning. The methodology consisted of a bibliographic study, involving the selection and analysis of publications addressing educational uses of AI and their effects on language-related practices. In the development, discussions were systematized regarding AI support for revision and rewriting stages, potential risks of substituting the act of writing, the reconfiguration of authorship criteria, and the need for teacher mediation and process-oriented assessment adjustments. In the final considerations, it was concluded that generative AI influenced writing instruction in an ambivalent way: it supported formal improvements and reflective opportunities when integrated with pedagogical intentionality and monitoring protocols but weakened authorship and learning when used without mediation and with exclusive focus on the final text. Further school-based studies were indicated to deepen evidence on learning and assessment outcomes.